# Tabular Data classification

*Tabular data classification*is a type of machine learning problem.

Each example consists of a list of

*features*, each of which is either*numeric*or*categorical:**Numeric**features*are integer or floating-point numbers.- Examples:
`[1, 5, -2, 3,...]`

`[20.1, 12.5, -2.2, ...]`

*Categorical features*are values from a finite list of options.- Examples:
`['dog', 'cat', 'cat', 'dog', ...]`

(options:`{'dog', 'cat'}`

)`[0, 1, 2, 0, ..]`

(options:`{0, 1, 2}`

)

- Note that categorical features can take integer values, as in the second example above. Unlike in the case of a number feature, however, the
*order*of the numbers is not meaningful.

The task is to predict a

*class label*from a finite list of possible classes, using the information in the features.